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"""
Example Airflow DAG for testing Google Dataflow to create pipelines.
"""
from __future__ import annotations
import os
from datetime import datetime
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.dataflow import (
DataflowCreatePipelineOperator,
DataflowDeletePipelineOperator,
DataflowRunPipelineOperator,
)
from airflow.providers.google.cloud.operators.gcs import (
GCSCreateBucketOperator,
GCSDeleteBucketOperator,
GCSSynchronizeBucketsOperator,
)
try:
from airflow.sdk import TriggerRule
except ImportError:
# Compatibility for Airflow < 3.1
from airflow.utils.trigger_rule import TriggerRule # type: ignore[no-redef,attr-defined]
DAG_ID = "dataflow_pipeline"
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
GCP_PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
GCP_LOCATION = "us-central1"
PIPELINE_NAME = f"{DAG_ID}-{ENV_ID}".replace("_", "-")
PIPELINE_JOB_NAME = f"{DAG_ID}-{ENV_ID}-job".replace("_", "-")
PIPELINE_TYPE = "PIPELINE_TYPE_BATCH"
RESOURCE_DATA_BUCKET = "airflow-system-tests-resources"
BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}".replace("-", "_")
FILE_NAME = "kinglear.txt"
TEMPLATE_FILE = "word-count.json"
TEMP_LOCATION = f"gs://{BUCKET_NAME}/temp"
GCS_PATH = f"gs://{BUCKET_NAME}/dataflow/{TEMPLATE_FILE}"
INPUT_FILE = f"gs://{BUCKET_NAME}/dataflow/{FILE_NAME}"
OUTPUT = f"gs://{BUCKET_NAME}/results/hello"
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "dataflow", "pipelines"],
) as dag:
create_bucket = GCSCreateBucketOperator(task_id="create_bucket", bucket_name=BUCKET_NAME)
move_files_to_bucket = GCSSynchronizeBucketsOperator(
task_id="move_files_to_bucket",
source_bucket=RESOURCE_DATA_BUCKET,
source_object="dataflow/pipelines",
destination_bucket=BUCKET_NAME,
destination_object="dataflow",
recursive=True,
)
# [START howto_operator_create_dataflow_pipeline]
create_pipeline = DataflowCreatePipelineOperator(
task_id="create_pipeline",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
body={
"name": f"projects/{GCP_PROJECT_ID}/locations/{GCP_LOCATION}/pipelines/{PIPELINE_NAME}",
"type": PIPELINE_TYPE,
"workload": {
"dataflowFlexTemplateRequest": {
"launchParameter": {
"containerSpecGcsPath": GCS_PATH,
"jobName": PIPELINE_JOB_NAME,
"environment": {"tempLocation": TEMP_LOCATION},
"parameters": {
"inputFile": INPUT_FILE,
"output": OUTPUT,
},
},
"projectId": GCP_PROJECT_ID,
"location": GCP_LOCATION,
}
},
},
)
# [END howto_operator_create_dataflow_pipeline]
# [START howto_operator_run_dataflow_pipeline]
run_pipeline = DataflowRunPipelineOperator(
task_id="run_pipeline",
pipeline_name=PIPELINE_NAME,
project_id=GCP_PROJECT_ID,
)
# [END howto_operator_run_dataflow_pipeline]
# [START howto_operator_delete_dataflow_pipeline]
delete_pipeline = DataflowDeletePipelineOperator(
task_id="delete_pipeline",
pipeline_name=PIPELINE_NAME,
project_id=GCP_PROJECT_ID,
trigger_rule=TriggerRule.ALL_DONE,
)
# [END howto_operator_delete_dataflow_pipeline]
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE
)
(
# TEST SETUP
create_bucket
>> move_files_to_bucket
# TEST BODY
>> create_pipeline
>> run_pipeline
# TEST TEARDOWN
>> delete_pipeline
>> delete_bucket
)
from tests_common.test_utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "teardown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests_common.test_utils.system_tests import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: contributing-docs/testing/system_tests.rst)
test_run = get_test_run(dag)